SEISMIC SIGNAL SELECTION USING BACK-PROPAGATED NEURAL NETWORKS

Authors

  • M. LAZARENKO
  • O. HERASYMENKO
  • N. OSTAPCHUK

Abstract

Feedforward, multi-layered, supervised network of artificial neurons is backpropagated to be used as classificator to discriminate automatically the seismic data flow into two classes: noise and not noise. The application of the algorithm to 1D seismic records is illustrated. 

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Published

2006-07-25

Issue

No. 38-39 (2006): Visnyk of Taras Shevchenko National University of Kyiv. Geology

Section

Articles

License

Copyright (c) 2006 М. А. ЛАЗАРЕНКО, О. А. ГЕРАСИМЕНКО, Н. М. ОСТАПЧУК

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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How to Cite

LAZARENKO, M., HERASYMENKO, O., & OSTAPCHUK, N. (2006). SEISMIC SIGNAL SELECTION USING BACK-PROPAGATED NEURAL NETWORKS. Visnyk of Taras Shevchenko National University of Kyiv. Geology, 38-39, 47-52. https://geology.bulletin.knu.ua/article/view/3308